2012/6/8 valentina presutti <[email protected]>: > Luca, I am forwarding this to stanbol mailing list, please next time use this > one. > If you're not yet subscribed, please do it :)
Good reflex to use the ML. Here is a copy of my reply: On 8 June 2012 12:34, Luca Cervone <[email protected]> wrote: > Dear Oliver, > I'm Luca Cervone from University of Bologna. > I will take part to the IKS meeting next week in which I'll present our > facebook game developed with the Prof. Valentina Presutti. > This game uses the stanbol engines in order to create a resource for the > sentiment analysis. > We are trying to improve the game and for this reason we are evaluating the > possibility to use the topic classification engine. > So we seen that the issue 197 (the rest API) is still open. Can you, kindly, > give us news about the status of the work? It mostly works but still lacks some web UI and documentation. > Is it possible to have a developing version of the API so we can install it > in our personal stanbol instance? Yes you can build and deploy the enhancer/engines/topic and enhancer/topic-web bundles on an stable or full distribution of stanbol. The you can use the webconsole to create a configuration for a new classification engine and a matching training set (leave the solr server parameters empty for a default configuration that should work). Then you can have a look at the topic-web java source for the JAX-RS endpoint to guess the HTTP API of the classifier model. You will need to use this HTTP API to import some possibly hierarchical target concepts into the model using either individual HTTP POST queries for each concept or a SKOS RDF taxonomy. Then use the API to upload many categorized text examples for each registered concept. Then another call to train the model. There are some python script that do this for IPTC NewsML files or a corpus of categorized articles extracted from DBpedia. http://svn.apache.org/repos/asf/incubator/stanbol/trunk/enhancer/topic-web/tools/ Here is sample training corpus pre-extracted using the dbpediakit tools: https://dl.dropbox.com/u/5743203/IKS/dbpedia/dbpediakit-output/dbpedia-taxonomy.tsv https://dl.dropbox.com/u/5743203/IKS/dbpedia/dbpediakit-output/dbpedia-examples.tsv.bz2 -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel
